- PhD in machine learning or computer science.
- Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
- A strong background in biology or medicine, enabling you to bridge the gap between advanced AI capabilities and complex scientific problems in drug discovery
- Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics), and with real world biological or chemical datasets and biological or chemistry software
- Experience in computational chemistry, bioinformatics, or related fields would be highly beneficial, along with a track record of applying AI to real-world scientific challenges
- Experience with multi-parameter optimization
- Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL
Culture and values
We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.
Thoughtful Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day.
Brave Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.
Determined Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we.
Together Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.
Creating an extraordinary company
We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact.
Hybrid working
It’s hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you’re in). If you have additional needs that would prevent you from following this hybrid approach, we’d be happy to talk through these if you’re selected for an initial screening call.
Please note that when you submit an application, your data will be processed in line with our privacy policy.
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